Flexible and scalable control of T cell memory by a reversible epigenetic switch (ATAC-seq)
Ontology highlight
ABSTRACT: In this study, we find that the Tcf7+ CD8 T cells present following acute challenge can form either from cells that maintain Tcf7 expression throughout activation or from cells that silence Tcf7 and reactivate it after stimulation removal. In this experiment, we asked whether both pathways can give rise to cells with genomic characteristics of memory. To do this, we activated naive CD8 T cells ex vivo for 2 days followed by 1 day of culture without TCR stimulation. On day 3, we sorted Tcf7-YFP high and low populations, all from a single CellTrace peak representing cells that had undergone the same number of divisions. The sorted populations were cultured for an additional 6 days and sorted again on day 9 by Tcf7-YFP levels. These samples, as well as control naive, antigen-experienced, and effector samples, were processed for ATAC-seq analysis.
Project description:In this study, we find that the Tcf7+ CD8 T cells present following acute challenge can form either from cells that maintain Tcf7 expression throughout activation or from cells that silence Tcf7 and reactivate it after stimulation removal. In this experiment, we asked whether both pathways can give rise to cells with genomic characteristics of memory. To do this, we activated naive CD8 T cells ex vivo for 2 days followed by 1 day of culture without TCR stimulation. On day 3, we sorted Tcf7-YFP high and low populations, all from a single CellTrace peak representing cells that had undergone the same number of divisions. The sorted populations were cultured for an additional 6 days and sorted again on day 9 by Tcf7-YFP levels. These samples, as well as control naive, antigen-experienced, and effector samples, were processed for RNA-seq analysis.
Project description:The precise timing and pathway of memory CD8+ T cells differentiation from naïve T cells have remained undetermined. We found the smaller cell-size and slower cell cycling cells were segregated from the proliferative larger cell-size activated T cell pool at the peak of infection. Gene signature of the smaller cell-size slower cycling cells and the large cell-size proliferative cells was compared to the signature of naïve, effector, central and effector memory CD8+ T cells. Total RNA samples were prepared from sorted populations of larger or smaller cell-sized cells from spleens of influenza virus PR8-OVA-infected mice on day 7 p.i. or from in vitro 7 days culture after stimulation with plate-bound anti-CD3ε (1.0 μg ml−1) and anti-CD28 mAb (0.5 μg ml−1). Effector T-cell control samples were prepared from SIINFEKL (100 ng ml−1) stimulated OT-I cells after 4 days of in vitro culture with rIL-2 (10 ng/ml) and sorted as CD8+CD44hiCD62Llo. Control bona fide effector memory and central memory T cells were sorted from the spleens of PR8-OVA-infected mice on day 42 p.i. Naive cells were sorted as CD8+CD44loCD62Lhi cells from uninfected C57BL/6 mice.
Project description:Effects of IL-4 on CD8 T cells functions are largely unknown. IL-4 induces survival and proliferation of CD8 T cells, but several studies suggest that IL-4 could also affect several functions of CD8 T cells such as cytotoxicity. Our team has shown that IL-4 repress the expression of Ccl5 in vitro. To define more precisely the impact of IL-4 on CD8 T cells, we performed a whole genome expression microarray analysis of naive and memory CD8 T cells cultured in presence or absence of IL-4. This approach allowed us to define the IL4-gene-expression signature on CD8 T cells. 18 samples were processed. Two populations of F5 naive CD8 T cells were FACS-sorted: samples from each population were incubated 20 hours with IL-7 in presence or absence of IL-4. Thus, a total of 6 “Naive” samples were processed. In addition, 4 populations of F5 TIM memory CD8 T cells were FACS-sorted: samples from 2 of these populations were incubated 20 hours in presence of IL-7 and/or IL-4, or in medium alone. Thus, 12 “Memory” samples were processed.
Project description:During an immune response, CD8 T cells fall along a gradient of memory potential, but the regulators of these fate decsisions are not well understood. We utlized Id3-GFP and Id2-YFP reporter mice to elucidate the role of Id3 and Id2 during early CD8 T cell differentiation by gene expression. Id3-GFP hi Id2-YFP int or Id3-GFP lo Id2-YFP hi OT-I cells were sorted into trizol at day 6 of VSV-OVA infection and analyzed by microarray
Project description:Naive T cells experience accumulation of TCR signaling in response to self-antigens in the steady state. However, how these signals influence the responsiveness of naive CD8+ T cells to subsequent agonist TCR stimulation remains incompletely understood. We investigated how naive CD8+ T cells that experienced relatively low or high levels of TCR signaling in response to self-antigens respond to stimulation with foreign antigens. A transcriptional reporter of Nr4a1 (Nur77-GFP) revealed substantial heterogeneity of the amount of TCR signaling naive CD8+ T cells accumulate in the steady state. To further understand the impact of differential TCR signaling on CD8 T cells we performed RNA-seq on naive Nur77-GFPhi and lo populations.
Project description:miRNAs play an important role in regulating CD8+ T cell response. We used the microarray approach to profile the miRNA signatures of naïve, day 5 effector, day 8 effector, and memory CD8+ T cells. We identified a miRNA signature associated with rapidly proliferating effector CD8+ T cells. CD8+ T cells from P14 TCR transgenic mice were transferred to C57BL6 recipients which were subsequently infected with LCMV Armstrong. Donor P14 CD8+ T cells were sorted on day 5, day 8, or >day 60 post-infection. Naïve P14 CD8+ T cells were sorted directly from naive P14 splenocytes. The total RNA including miRNAs was extracted from sorted samples, labeled, and hybridized to Agilent Mouse miRNA microarray.
Project description:The PI3K/Akt signaling pathway impacts various aspects of CD8 T cell homeostasis, such as effect versus memory cell differentiation, during viral infection. We used microarrays to determine which downstream molecules were affected and what other signaling pathways were interconnected with the Akt pathway by constitutive activation of Akt in LCMV-infected CD8 T cells. Splenocytes from naive P14/WT or P14/Akt mice were stained with anti-CD8 and anti-Ly5.1, and CD8 T cells were sorted using a FACSAria II instrument. Purified Ly5.1+ CD8 T cells from P14/WT or P14/Akt mice were transferred into B6 mice, which were subsequently infected with LCMV Armstrong. At day 8 post infection, splenocytes were stained with anti-CD8, anti-Ly5.1, anti-KLRG1, and anti-CD127. Following staining, short-lived effector cells (SLECs) and memory precursor effector cells (MPECs) were sorted using the FACSAria II instrument; the purity of the sorted cells was >95%. A total of 5 samples were analyzed, including WT naive, WT SLEC, WT MPEC, Akt naive and Akt SLEC.
Project description:We isolated splenic NK cells and cultured them for 3 days in 100 ng/ml IL-15. Next, we stimulated the cells with plate-bound anti-NK1.1 for 6 hours and sorted YFP+ (IFNg+) and YFP- (IFNg-) populations. We then performed gene expression profiling analysis using data obtained from RNA-seq from unstimulated, YFP+ or YFP- NK cells.
Project description:Memory T cells respond to stimulation with more rapid expression of effector cell functions than their naM-CM-/ve counterparts, yet the gene expression signature underlying this enhanced recall response is not known. Therefore, we performed comprehensive, whole-genome expression profiling of murine memory CD8 T cells before and shortly after ex vivo stimulation. We compared this differential expression profile to its counterpart from stimulated naive cells. Given that memory cells arise from naive cells, the quiescent state of both cell populations prior to stimulation, and the early time point analyzed (four hours post-stimulation), it was possible that the stimulation-induced changes in gene expression were identical between the two populations. While there was a high degree of overlap, we found that the majority of up-regulated genes were more highly induced following stimulation of memory cells. This more robust increase in transcript levels was observed for a functionally diverse set of genes, including cytokines, chemokines, amino acid metabolic enzymes and transporters, transcription factors and regulators of RNA processing. We also identified the unique, stimulation-induced signatures of naive and memory CD8 T cells and found that the former was enriched for factors involved in regulating chromatin modifications. Specifically, we found that Hdac 5,7 and 8 transcript levels were rapidly down-regulated following stimulation of naive cells, which correlated with an increase in their total level of acetylated histone H3 (AcH3). This was in contrast to stimulated memory cells, which had higher levels of total AcH3 ex vivo that did not change following short-term stimulation. Furthermore, the unique stimulation-induced expression profile of memory cells was enriched for factors involved in regulating transport of molecules between the nucleus and cytoplasm, including multiple members of the nuclear pore complex. Together, these results support a model whereby the chromatin modifications that occur during the differentiation of naM-CM-/ve cells into memory cells are preserved in resting memory populations, facilitating their more robust re-activation of a functionally diverse set of genes that contribute to rapid recall of effector functions. NaM-CM-/ve (CD44lo) and memory phenotype (CD44hi) CD8 T cells from 7-wk old female B6 mice were FACS-purified and cultured in vitro for four hours in the presence or absence of PMA and ionomycin. Total RNA was purified from un-stimulated (resting) naM-CM-/ve, resting memory, stimulated naive, and stimulated memory cells and hybridized to individual single-color arrays. This purification and stimulation protocol was performed four independent times.
Project description:We use bulk RNA sequencing of sorted cells to characterize the gene expression profiles of renal dendritic cell (DC) subsets, cDC1 and cDC2, as well as MHCII+CD64+ F4/80hi and MHCII+CD64+ CD11bhi cells. Splenic DCs and red pulp macrophages serve as reference populations for a macrophage-like or DC-like phenotype. By sorting YFP+/YFP- F4/80hi or YFP+/YFP- CD11bhi cells from Clec9a-Cre Rosa-YFP mice we aim to reveal transcriptional differences between YFP-labelled and unlabelled cells. We showed that F4/80hi cells resemble macrophages on a transcriptional level, despite their DC origin, and that renal CD11bhi cells are a transcriptionally unique subset. However, we were not able to reveal differences between YFP+ and YFP- populations.